The Role Of Body Mass Index In Survival Outcome For Lymphoma Patients: US Intergroup Experience
Bibliographic record
Abstract
Abstract Introduction The role of body mass index (BMI) impacting clinical outcome among lymphoma patients is controversial. Two recent studies suggest that increased BMI is associated with significantly improved survival. In this study the association between BMI at study entry and failure-free survival (FFS) and overall survival (OS) was evaluated in three phase III Eastern Cooperative Oncology Group-led trials, among patients with DLBCL (E4494), follicular lymphoma (FL) (E1496) and Hodgkin's lymphoma (HL) (E2496). Patients and Methods 537 patients with DLBCL, 730 patients with HD and 282 patients with FL were included in the analysis. BMI was calculated as weight (kilograms) divided by the square of height (meters), using data at study entry. BMI was analyzed both as continuous and categorical variables (underweight <18.5 kg/m2, normal weight: 18.5 to < 25 kg/ m2, overweight: 25 to < 30 kg/ m2, and obese :≥ 30 kg/ m2).The underweight group was excluded due to low (< 2%) prevalence. Baseline patient and clinical characteristics, treatment received and clinical outcomes were compared across BMI categories. PFS was defined as the time from study entry to relapse, progression, or death. OS was measured from study entry to death of any cause. The log-rank test and Cox regression models was used to check the association. The association between BMI and FFS/OS was also independently assessed among patients treated with rituximab. A sensitivity analysis was performed excluding patients with significant weight loss at baseline. Results Among patients with DLBCL, HL and FL, the median age was 70, 33 and 56; 29%, 29% and 37% were obese and 38%, 27% and 37% were overweight, respectively. Age was significantly different among BMI groups in all three studies. Higher BMI groups tended to have better prognosis at study entry among DLBCL and HL patients. BMI was not associated with clinical outcome, with p-values of 0.89, 0.30 and 0.40 for FFS, and p-values of 0.64, 0.67 and 0.09 for OS, for patients with DLBCL, HL and FL, respectively (Figure 1). In multivariate analysis adjusting for other clinical factors, BMI remains an insignificant predictor for all three histologies (Table 1). When limiting to patients treated with rituximab, the association remains non-significant for both FL patients (p=0.92 for PFS, p=0.36 for OS) and DLBCL patients (Figure 2). A subset analysis of males with DLBCL treated on R-CHOP, which matched the study cohort used in a recent report (Carson et al, 2012), revealed no differences in FFS (p=0.48) or OS (p=0.58) (Figure 2). Sensitivity analysis excluding patients with weight loss at study entry resulted in similar findings. Conclusion BMI was not significantly associated with clinical outcomes among patients with DLBCL, HL or FL, in three prospective phase III clinical trials. The findings contradict some previous reports of similar investigations. Further work is required to understand the observed discrepancies. Disclosures: Horning: Genentech: Employment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".